Titlebook: Business Analytics; Data Science for Bus Walter R. Paczkowski Book 2021 Springer Nature Switzerland AG 2021 data science.machine learning.b

披肩

Walter R. PaczkowskiUses case studies to illustrate concepts.Presents examples using Python in the context of Jupyter notebooks with Programming Literacy examples.Features appendices with technical details

prosperity

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Exclude

Data Sources, Organization, and Structuresever, that you need data first is too simplistic and trivial. Where data originate, how you get them, and what you do with them, that is, how you manipulate them, before you begin your work is important to address.

獨裁政府

Obloquy

Advanced Data Handling: Preprocessing Methodso or very few issues as I noted at the beginning of Chap. .. Unfortunately, real world data do not agree with this paradigm. They are, to say the least, messy. They have missing values, are disorganized relative to what you need to do, and are just, well, a mess. Before any meaningful work is done, you have to . or, better yet, . your messy data.

epicardium

Omniscient

Time Series Analysissiness data sets. The data, a ., could be for each second because of sensor readings, each minute for a production process, daily for accounting recording, monthly for sales and revenue processing and reporting, quarterly for financial reporting to legal and regulatory agencies, or annually for shareholder meetings.

走調

Visual-Field

Classification with Supervised Learning Methodss. Recall that “prediction” is a broad label that includes forecasting as a subset: all forecasts are predictions but not all predictions are forecasts. Predicting in general is a very important function of Business Data Analytics which is why I spent so much time on it.

使人入神

Food and Identity in Early Rabbinic JudaismSpoiler-alert: . (.), the focus of this book, is solely concerned with one task, and one task only: to provide the richest information possible to decision makers.